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Updated: Aug 1, 2026
Visualization of Intensity Levels to Reduce the Gap Between Self-Reported and Directly Measured Physical Activity
Published on: March 7, 2019
Normative Peak Physical Activity Values for Monitor-Independent Movement Summary Units: National Health and Nutrition
Scott W Ducharme1, James D Pleuss2,3, Dusty S Turner2,4
1Department of Kinesiology, California State University, Long Beach, Long Beach, CA, USA.
Background:
The most recent physical activity (PA) monitor data from the US National Health and Nutrition Examination Survey (NHANES) were processed using a novel monitor-independent movement summary (MIMS) algorithm. To date, few studies have utilized these data, likely due to a general unfamiliarity with MIMS-related metrics. The purpose of this study was to establish normative values for peak MIMS metrics as measures of free-living PA intensity and natural ambulatory effort.
Methods:
Data from the National Health and Nutrition Examination Survey 2011-2012 and 2013-2014 survey cycles were used, including 8729 individuals aged 20-80+ years. MIMS data were obtained from wrist-worn accelerometers worn for at least 1 valid day (<5% nonwear time per day). Peak-1MIMS (ie, the highest 1-min MIMS value within a day) and Peak-30MIMS (ie, the average of the 30 highest 1-min MIMS values) were obtained, averaged across all valid days, and reported as sample-weighted means (95% confidence intervals), and across 5th to 95th percentiles.
Results:
Mean (95% confidence interval) values for Peak-1MIMS and Peak-30MIMS were 59.9 (59.2-61.6) and 42.9 (42.4-43.3) MIMS/minute, respectively. Both peak metrics declined across the adult lifespan. Men displayed greater Peak-1MIMS, while Peak-30MIMS was similar between sexes. Both MIMS metrics trended lower with increasing body mass index.
Conclusion:
We provide normative values for peak MIMS metrics which reflect PA intensity/effort. We also developed an R-Shiny App whereby users can input age, sex, body mass index category, and MIMS metrics to determine individual-specific MIMS percentile values. Given the universal nature of the MIMS algorithm, these population representative data may be useful as a reference data set for device-based PA surveillance within the United States and for comparison globally.
